A Wavelet Coherence Analysis: Contagion in Emerging Countries Stock Markets

This study aims to investigate the financial contagion during and after Greek Crisis to observe the impact on global economy. Financial contagion may affect the portfolio risk management, the formulation of monetary, fiscal policy, strategic asset allocation and pricing. To analyse the contagion after Greek Crisis, the co-movements of six stock exchange markets have been studied for an 8-year term. For this study between countries’ time series, bivariate wavelet technique called wavelet coherence is employed, and Matlab 2016a wavelet tool is used for the analysis. Daily closing prices of stock market indices of six countries, Greece (ASE), UK (FTSE100), Germany (DAX), Hungary (BUX), Poland (WIG) and Turkey (BIST100) are used in this analysis between 06 March 2009 and 28 February 2017.This paper targets to show if there is a certain sign for a co-movement between markets during and after Greek Debt Crisis. Therefore, it eventually sets out the benefits or harm of integration in the financial markets by using Wavelet Method. This study contributes the literature by analyzing the effects of contagion among stock markets by using wavelet method. This analysis has been filling the gap in the literature by employing a new technique to explain leverage effect with financial time series data. As wavelet tool displays the leverage effect by comparing crisis and non-crisis periods, the study supports the idea that convergence is adversely affecting the connected markets. According to the results of the study, the contagion is high especially during crisis within European financial markets. whereas positive improvements have less impact on markets

Improving A*OMP: Theoretical and Empirical Analyses With a Novel Dynamic Cost Model

Best-first search has been recently utilized for compressed sensing (CS) by the A* orthogonal matching pursuit (A*OMP) algorithm. In this work, we concentrate on theoretical and empirical analyses of A*OMP. We present a restricted isometry property (RIP) based general condition for exact recovery of sparse signals via A*OMP. In addition, we develop online guarantees which promise improved recovery performance with the residue-based termination instead of the sparsity-based one. We demonstrate the recovery capabilities of A*OMP with extensive recovery simulations using the adaptive-multiplicative (AMul) cost model, which effectively compensates for the path length differences in the search tree. The presented results, involving phase transitions for different nonzero element distributions as well as recovery rates and average error, reveal not only the superior recovery accuracy of A*OMP, but also the improvements with the residue-based termination and the AMul cost model. Comparison of the run times indicate the speed up by the AMul cost model. We also demonstrate a hybrid of OMP and A?OMP to accelerate the search further. Finally, we run A*OMP on a sparse image to illustrate its recovery performance for more realistic coefcient distributions

Non-Natural Born lecturers: How to survive teaching in Dutch higher education

[EN] Teaching in Higher Education Institutions (HEI) requests training and skills as researching. Unfortunately, on an international level the teaching training programme is not always crystal and clear, or even worse, not requested. Often researchers are asked to provide lectures without receiving proper formation. This approach creates sensible depletion in the educational quality. Offering an overview on how the Dutch HEIs are tackling the problem, the aim of this study is twofold: (i) presenting the University Teaching Qualification (UTQ) from a career development perspective and (ii) giving a qualitative evaluation of the entire process from the point of view of UTQ supervisors and lecturers. Finally concluding the relevance of such a professionalization programme.http://ocs.editorial.upv.es/index.php/HEAD/HEAD18Oude Alink, C.; Martinetti, A.; Karahanoğlu, A.; Hahnen-Florijn, M. (2018). Non-Natural Born lecturers: How to survive teaching in Dutch higher education. Editorial Universitat Politècnica de València. 1205-1213. https://doi.org/10.4995/HEAD18.2018.8177OCS1205121

Search-based methods for the sparse signal recovery problem in compressed

The sparse signal recovery, which appears not only in compressed sensing but also in other related problems such as sparse overcomplete representations, denoising, sparse learning, etc. has drawn a large attraction in the last decade. The literature contains a vast number of recovery methods, which have been analysed in theoretical and empirical aspects. This dissertation presents novel search-based sparse signal recovery methods. First, we discuss theoretical analysis of the orthogonal matching pursuit algorithm with more iterations than the number of nonzero elements of the underlying sparse signal. Second, best-first tree search is incorporated for sparse recovery by a novel method, whose tractability follows from the properly defined cost models and pruning techniques. The proposed method is evaluated by both theoretical and empirical analyses, which clearly emphasize the improvements in the recovery accuracy. Next, we introduce an iterative two stage thresholding algorithm, where the forward step adds a larger number of nonzero elements to the sparse representation than the backward one removes. The presented simulation results reveal not only the recovery abilities of the proposed method, but also illustrate optimal choices for the step sizes. Finally, we propose a new mixed integer linear programming formulation for sparse recovery. Due to the equivalency of this formulation to the original problem, the solution is guaranteed to be correct when it can be solved in reasonable time. The simulation results indicate that the solution can be found easily under some reasonable assumptions, especially for signals with constant amplitude nonzero elements

Is it just a score? Understanding Training Load Management Practices Beyond Sports Tracking

Training Load Management (TLM) is crucial for achieving optimal athletic performance and preventing chronic sports injuries. Current sports trackers provide runners with data to manage their training load. However, little is known about the extent and the way sports trackers are used for TLM. We conducted a survey (N=249) and interviews (N=24) with runners to understand sports tracker use in TLM practices. We found that runners possess some understanding of training load and generally trust their trackers to provide accurate training load-related data. Still, they hesitate to strictly follow trackers’ suggestions in managing their training load, often relying on their intuitions and body signals to determine and adapt training plans. Our findings contribute to SportsHCI research by shedding light on how sports trackers are incorporated into TLM practices and providing implications for developing trackers that better support runners in managing their training load

A Nonsurgical Approach to Treatment of High-Angle Class II Malocclusion

The bite opening effects of orthodontic appliances often cause a downward and backward mandibular rotation that only exacerbates the malocclusion. Successful orthodontic treatment of a high angle, Class II, Division 1 malocclusion requires careful consideration of the vertical dimension during treatment planning. This case report shows an individualized treatment approach to a patient with high angle Class II malocclusion

Failure to mobilize cognitive control for challenging tasks correlates with symptom severity in schizophrenia

Deficits in the adaptive, flexible control of behavior contribute to the clinical manifestations of schizophrenia. We used functional MRI and an antisaccade paradigm to examine the neural correlates of cognitive control deficits and their relations to symptom severity. Thirty-three chronic medicated outpatients with schizophrenia and 31 healthy controls performed an antisaccade paradigm. We examined differences in recruitment of the cognitive control network and task performance for Hard (high control) versus Easy (low control) antisaccade trials within and between groups. We focused on the key regions involved in ‘top-down’ control of ocular motor structures – dorsal anterior cingulate cortex, dorsolateral and ventrolateral prefrontal cortex. In patients, we examined whether difficulty implementing cognitive control correlated with symptom severity. Patients made more errors overall, and had shorter saccadic latencies than controls on correct Hard vs. Easy trials. Unlike controls, patients failed to increase activation in the cognitive control network for Hard vs. Easy trials. Reduced activation for Hard vs. Easy trials predicted higher error rates in both groups and increased symptom severity in schizophrenia. These findings suggest that patients with schizophrenia are impaired in mobilizing cognitive control when presented with challenges and that this contributes to deficits suppressing prepotent but contextually inappropriate responses, to behavior that is stimulus-bound and error-prone rather than flexibly guided by context, and to symptom expression. Therapies aimed at increasing cognitive control may improve both cognitive flexibility and reduce the impact of symptoms

Analytical form of Shepp-Logan phantom for parallel MRI

ABSTRACT We present an analytical form of ground-truth k-space data for the 2-D Shepp-Logan brain phantom in the presence of multiple and non-homogeneous receiving coils. The analytical form allows us to conduct realistic simulations and validations of reconstruction algorithms for parallel MRI. The key contribution of our work is to use a polynomial representation of the coil's sensitivity. We show that this method is particularly accurate and fast with respect to the conventional methods. The implementation is made available to the community

Grand Challenges in SportsHCI

The field of Sports Human-Computer Interaction (SportsHCI) investigates interaction design to support a physically active human being. Despite growing interest and dissemination of SportsHCI literature over the past years, many publications still focus on solving specific problems in a given sport. We believe in the benefit of generating fundamental knowledge for SportsHCI more broadly to advance the field as a whole. To achieve this, we aim to identify the grand challenges in SportsHCI, which can help researchers and practitioners in developing a future research agenda. Hence, this paper presents a set of grand challenges identified in a five-day workshop with 22 experts who have previously researched, designed, and deployed SportsHCI systems. Addressing these challenges will drive transformative advancements in SportsHCI, fostering better athlete performance, athlete-coach relationships, spectator engagement, but also immersive experiences for recreational sports or exercisemotivation, and ultimately, improve human well-being